Open AccessDENSE IMAGE MATCHING FOR MARS EXPRESS HRSC IMAGERY BASED ON PRECISE POINT PREDICTION METHOD
Author(s) -
X. Geng,
Q. Xu,
J. Miao,
Y. F. Hou,
S. Xing,
C. Z. Lan
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b4-391-2016
Subject(s) - mars exploration program , pixel , mean squared error , computer science , point (geometry) , artificial intelligence , satellite imagery , remote sensing , matching (statistics) , computer vision , geology , image (mathematics) , mathematics , geometry , statistics , physics , astronomy
Currently, Mars Express HRSC imagery is an essential data source to derive high accuracy Mars topographic data. In view of the characteristics of Martian surface satellite imagery, a dense image matching scheme for HRSC imagery based on precise point prediction method is proposed. The image matching strategies of our method are elaborated in detail. Based on the proposed method, DEM and DOM of Martian surface are derived and compared with those published by ESA. The experiment results show that the root mean square error in planar direction is about three pixels, while the root mean square error in height direction is about one pixel. Moreover, the mean square error in plane direction show a certain systematic error and the reasons are analysed. Experiment results also demonstrate that the point prediction accuracy for corresponding points is up to 1–3 pixels.